Modeling Expectation Formation Involving Several Sources of Information

Abstract. Experimental studies of expectation formation of subjects are predominantly limited to the prediction of one single time series despite the practical relevance of expectations in situations with multiple sources of information. In this paper, we report on an experiment in which subjects are given time series (indicators) as additional information for the judgemental forecast of a stationary time series. The quality and the number of these indicators are varied in three versions of a forecasting experiment. We explore the effects on forecasting accuracy and we test the average forecasts of the subjects for consistency with the rational expectations hypothesis. A simple heuristic is presented that explains the average forecasting behavior better than the rational expectations if indicators are presented to the subjects. It is demonstrated by a simulation study that this result is representative for the considered stationary stochastic processes.     

Assessment of the effect of the financial crisis on agents’ expectations through symbolic regression

Agents’ perceptions on the state of the economy can be affected during economic crises. Tendency surveys are the main source of agents’ expectations. The main objective of this study is to assess the impact of the 2008 financial crisis on agents’ expectations. With this aim, we evaluate the capacity of survey-based expectations to anticipate economic growth in the United States, Japan, Germany and the United Kingdom. We propose a symbolic regression (SR) via genetic programming approach to derive mathematical functional forms that link survey-based expectations to GDP growth. By combining the main SR-generated indicators, we generate estimates of the evolution of GDP. Finally, we analyse the effect of the crisis on the formation of expectations, and we find an improvement in the capacity of agents’ expectations to anticipate economic growth after the crisis in all countries except Germany.     

Leading indicators of fiscal distress: evidence from extreme bounds analysis

Early warning systems (EWSs) are widely used to assess a country’s vulnerability to fiscal distress. A fiscal distress episode is identified as a period when government experiences extreme funding difficulties. Most EWSs employ a specific set of only fiscal leading indicators predetermined by the researchers, which casts doubt on their robustness. We revisit this issue using extreme bounds analysis, which allows identifying robust leading indicators of fiscal distress from a large set. A robust leading indicator’s effect does not strongly depend on the model specification. Consistent with the theoretical predictions of latest generation crisis models, we find that both fiscal and non-fiscal leading indicators are robust. In addition, we find that a fiscal vulnerability indicator based on fiscal and non-fiscal leading indicators offers a 29% gain in predictive power compared to a traditional one based only on fiscal leading indicators. This suggests that both fiscal and non-fiscal leading indicators should be taken into account when assessing country’s vulnerability to fiscal distress.     

The information content of market-based measures for the long-term inflation expectations of professionals: evidence from a midas analysis

Long-term inflation expectations taken from the Survey of Professional Forecasters are a major source of information for monetary policy. Unfortunately, they are published only on a quarterly basis. This article investigates the daily information content of market-based measures, such as inflation-linked swaps and breakeven inflation rates, for the next survey outcome. Using a mixed data sampling approach, we find that professionals account for the daily dynamics of market-based measures when they submit their long-term inflation expectations. We propose a daily indicator of professionals’ inflation expectations that outperforms alternative indicators that ignore the high-frequency dynamics of market-based measures. To illustrate the usefulness of the new indicator, we provide new evidence on the (re-)anchoring of U.S. inflation expectations.     

Inflation literacy and inflation expectations: Evidence from Austrian household survey data

Inflation expectations are known to be quite heterogeneous across agents. We investigate whether this heterogeneity is primarily due to differences in people’s understanding of the inflation process and of the goals and intentions of the central bank. Using micro data from a survey conducted among 2000 Austrian households, we construct an indicator of “inflation literacy” from several questions on people’s knowledge about different aspects of inflation. We find that this indicator helps explain both the level and the uncertainty of inflation expectations: Households with relatively higher levels of inflation literacy tend to have lower and more accurate short-term and long-term inflation expectations. Interestingly, however, they are less certain about their inflation expectations than people with lower levels of inflation literacy. We also find that people’s trust in the central bank and in its ability to maintain price stability significantly dampens their inflation expectations.     

Trust and reciprocity: extensions and robustness of triadic design

Our paper reconsiders the triadic design proposed by Cox (Games and Economic Behavior 46:260–281, 2004) to identify trust and reciprocity in investment games. Specifically, we extend the design in two directions. First, we collect information on investors’ choices by using both the direct-response (as does Cox) and strategy methods. Using the latter, we are able to condition reciprocity on initial inequality, which is endogenous when investigating reciprocity. We demonstrate that the triadic design provides evidence for reciprocity once that initial inequality is considered. Second, we elicit expectations and test their coherence with the triadic outcomes. By examining the relationship between trust actions and expected gains, we analyze whether investors’ expectations are consistent with their behavior. Finally, we test for the existence of an emotional bias, i.e., whether expectation mismatches induce trustees to change actual choices from the planned ones.     

Determinants and consequences of soft budget constraintsAn empirical analysis using enterprise‐level data in transition countries1

This paper presents empirical work grounded in the soft budget constraint (SBC) literature. A loan is soft when a bank cannot commit the enterprise to hold to a fixed initial budget and/or the timing of repayment. Using data collected by the European Bank for Reconstruction and Development (EBRD) (Business Environment and Enterprise Performance Survey (BEEPS), 2002) in 26 transition economies, we analyze the determinants of managers’ expectations of having a soft loan. In particular, we find that managers’ expectations are lower when the initial financing requires collateral, and higher for larger firms and when firms had recently experienced financial distress. We also provide evidence that managers’ expectations influence their price responsiveness.     

Macroeconomic expectations and time varying heterogeneity:evidence from individual survey data

ABSTRACT

The goal of this paper is to investigate forecast heterogeneity and time variability in the formation of expectations using disaggregated monthly survey data on macroeconomic indicators provided by Bloomberg from June 1998 to August 2017. We show that our panel of forecasters are not rational and are moderately heterogeneous and thus confirm that previously well-established results on asset prices hold for macroeconomic indicators. We propose a flexible hybrid forecast model defined at any time as a combination of the extrapolative, regressive, adaptive and interactive heuristics. Controlling for endogenous structural breaks, we find that experts adjust their forecast behaviour at any time with some inertia in extrapolative and adaptive profiles. Changes in the formation of expectations are triggered mostly by financial shocks, and uncertainty is dealt with by using complex processes in which the fundamentalist component overweighs chartist activity. Forecasters whose models combine different relevant rules and display high temporal flexibility provide the most accurate forecasts. Authorities can then stabilize the domestic markets by encouraging fundamentalists’ forecasts through increased transparency policy.     

A new consensus-based unemployment indicator

In this study we present a novel approach to measure the level of consensus among agents’ expectations. The proposed framework allows us to design a positional indicator that gives the percentage of agreement between survey expectations. While other aggregation methods such as the balance, which is constructed as the difference between the percentages of respondents giving positive and negative replies, explicitly omit the neutral information, the proposed metric allows synthesizing the information coming from all response categories, including the percentage of respondents who do not expect any change. In order to assess the performance of the proposed measure of consensus, we compare its ability to track the evolution of unemployment to that of the balance in eight European countries. With this aim, we scale both measures to generate one-period ahead forecasts of the unemployment rate. We find that the consensus-based unemployment indicator outperforms the balance in all countries except Denmark and Sweden, which suggests that the level of agreement among agents’ expectations is a good predictor of unemployment.     

Quantification and characteristics of household inflation expectations in Switzerland

Inflation expectations are a key variable in conducting monetary policy. However, these expectations are generally unobservable and only certain proxy variables exist, such as surveys on inflation expectations. This article offers guidance on the appropriate quantification of household inflation expectations in the Swiss Consumer Survey, where answers are qualitative in nature. We apply and evaluate different variants of the probability approach and the regression approach; we demonstrate that models that include answers on perceived inflation and allow for time-varying response thresholds yield the best results; and we show why the originally proposed approach of Fluri and Spörndli (1987) has resulted in heavily biased inflation expectations since the mid-1990s. Furthermore, we discuss some of the key features of Swiss household inflation expectations, i.e. the fact that there has been a shift in expectation formation since 2000 (expectations are better anchored and less adaptive, and there is lower disagreement of expectations). We suggest that this may be linked to the Swiss National Bank’s adjustment of its monetary policy framework around this time. In addition, we outline how expectation formation in Switzerland is in line with the sticky information model, where information disseminates slowly from professional forecasters to households.     

South African stock return predictability in the context data mining: The role of financial variables and international stock returns

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the t-statistic corresponding to the slope coefficient in a predictive regression model for in-sample predictions, while for the out-of-sample, the MSE-F and the ENC-NEW tests statistics with good power properties were utilised. To guard against data mining, a bootstrap procedure was employed for calculating the critical values of both the in-sample and out-of-sample test statistics. Furthermore, we use a procedure that combines in-sample general-to-specific model selection with out-of-sample tests of predictive ability to further analyse the predictive power of each financial variable. Our results show that, for the in-sample test statistic, only the stock returns for our major trading partners have predictive power at certain short and long run horizons. For the out-of-sample tests, the Treasury bill rate and the term spread together with the stock returns for our major trading partners show predictive power both at short and long run horizons. When accounting for data mining, the maximal out-of-sample test statistics become insignificant from 6-months onward suggesting that the evidence of the out-of-sample predictability at longer horizons is due to data mining. The general-to-specific model shows that valuation ratios contain very useful information that explains the behaviour of stock returns, despite their inability to predict stock return at any horizon. The model also highlights the role of multiple variables in predicting stock returns at medium- to long run horizons.     

Efficiency and formation of expectations: evidence from the European investment survey

The European Commission conducts an annual survey regarding planned and realized business fixed investment across various manufacturing sectors in Euroland. In this study we investigate the predictive content of survey-based expectations on investment. In addition, we empirically test the rationality of respondents both in a time series as well as in a panel context. According to our results, based on pooling the data, efficiency is rejected since expectations are biased predictors of actual outcomes. Furthermore, expectations revisions are found to be correlated with components of the information set known at the time of decision making. Finally, our results qualify regressive expectations as the mechanism that more adequately describes the formation of expectations.     

Forecasting GDP all over the world using leading indicators based on comprehensive survey data

Comprehensive and international comparable leading indicators across countries and continents are rare. In this paper, we use a free and instantaneous available source of leading indicators, the ifo World Economic Survey (WES), to forecast growth of Gross Domestic Product (GDP) in 44 countries and three country aggregates separately. We come up with three major results. First, for more than three-fourths of the countries or country-aggregates in our sample, a model containing one of the major WES indicators produces on average lower forecast errors compared to a benchmark model. Second, the most important WES indicators are either the economic climate or the expectations on future economic development for the next six months. And third, adding the WES indicators of the main trading partners leads to a further increase in forecast accuracy in more than 50% of the countries. It seems therefore reasonable to incorporate economic signals from the domestic economy’s main trading partners.     

Coordination on saddle-path solutions: the eductive viewpoint—linear multivariate models

We examine local strong rationality (LSR) in multivariate models with both forward-looking expectations and predetermined variables. Given hypothetical common knowledge restrictions that the dynamics will be close to those of a specified minimal state variable solution, we obtain eductive stability conditions for the solution to be LSR. In the saddlepoint stable case the saddle-path solution is LSR provided the model is structurally homogeneous across agents. However, the eductive stability conditions are strictly more demanding when heterogeneity is present, as can be expected in multisectoral models. Heterogeneity is thus a potentially important source of instability even in the saddlepoint stable case.     

Understanding Markov-switching rational expectations models

We develop a set of necessary and sufficient conditions for equilibria to be determinate in a class of forward-looking Markov-switching rational expectations models and we develop an algorithm to check these conditions in practice. We use three examples, based on the new-Keynesian model of monetary policy, to illustrate our technique. Our work connects applied econometric models of Markov-switching with forward looking rational expectations models and allows an applied researcher to construct the likelihood function for models in this class over a parameter space that includes a determinate region and an indeterminate region.     

Rationality tests in the presence of instabilities in finite samples

The importance of expectations in modern macroeconomic models and in particular of policy makers expectations for forward looking policy rules has generated a lot of interest in time series of professional forecasts (including central bank staff forecasts). This has spawned a large literature on the evaluation of forecasts that are not model based or where the model is unknown. Although, the available time series of historical forecasts are typically short, this literature has so far mostly disregarded the small sample properties of the proposed tests and estimators. In this paper we fill this gap in the literature, focusing on a set of recently proposed rationality tests for unstable environments. Using a Monte Carlo study we demonstrate that the asymptotic tests are substantially oversized in finite samples including any sample size that is practically available. We provide finite sample adjusted critical values, that allow those tests to be properly applied to sample sizes of typically available forecasts such as the Survey of Professional Forecasters, the Federal Open Market Committee. The critical values we provide will help to avoid false rejections using those data.     

Constructing a new leading indicator for unemployment from a survey among German employment agencies

The article investigates the predictive power of a new survey implemented by the Federal Employment Agency (FEA) for forecasting German unemployment in the short run. Every month, the CEOs of the FEA’s regional agencies are asked about their expectations of future labour market developments. We generate an aggregate unemployment leading indicator that exploits serial correlation in response behaviour through identifying and adjusting temporarily unreliable predictions. We use out-of-sample tests suitable in nested model environments to compare forecasting performance of models including the new indicator to that of purely autoregressive benchmarks. For all investigated forecast horizons (1, 2, 3 and 6 months), test results show that models enhanced by the new leading indicator significantly outperform their benchmark counterparts. To compare our indicator to potential competitors, we employ the model confidence set. Results reveal that models including the new indicator perform very well at the 10% level.     

Youth labor market expectations and job matching in sub-Saharan Africa: evidence from school-to-work transition surveys

In this paper, we investigate the factors that influence youth labour market expectations and outcomes. We also perform a job matching exercise to understand youth labour market dynamics in Sub-Saharan Africa. Our results show that youth education is an influential factor of youth employment expectations and employment, ceteris paribus. Higher educational attainments have a great impact on expecting and securing better jobs, particularly in the technical and professional fields. Youth with low educational attainments, particularly primary education and lower, have a higher tendency to expect to be employed in occupations with low job complexity. Our results indicate a severe job-skill mismatch in all occupational categories, both before and after the youth’s transition into the labour market. Using education as the only selection criterion, we found that less than 10 per cent of employment expectations match with skills required while 55 per cent and 34 per cent are under or over-educated for the jobs expected, respectively. Over and under education is a notable feature in youth labour markets in Sub-Saharan Africa. About 47 per cent of employed youth in the sample are overqualified for their respective jobs while 28 per cent are under qualified.     

Estimating domestic content in China’s exports: Accounting for a dual-trade regime

This paper identifies the heterogeneity issue as a key challenge that is central to but not fully addressed when measuring global value chains. To resolve this issue, we propose an extended input-output model that is consistent with the theoretical framework of heterogeneous firms. Empirically, we use China as a prominent example of a country that is engaged in both normal trade and the processing trade under a dual-trade regime, and we synthesize methods for constructing China’s extended input-output dataset for the period 1997 to 2015. Our results show that when alternative generic datasets are used, this is likely to result in overestimating the domestic content in China’s exports by as much as 44%, compared to a model that uses an extended database that incorporates production heterogeneity, as does the one in this study. This paper’s proposed methodology and rich dataset may be useful to a wider range of empirical applications.